Peter A. Flach

ORCID

Publication Activity (10 Years)

Years Active: 1989-2023
Publications (10 Years): 87

Top Venues

Publications

Torty Sivill, Peter A. Flach
Shapley Sets: Feature Attribution via Recursive Function Decomposition. CoRR (2023)
Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. CoRR (2023)
Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. PerCom Workshops (2023)
Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach, Ian Craddock
An active semi-supervised deep learning model for human activity recognition. J. Ambient Intell. Humaniz. Comput. 14 (10) (2023)
Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Peter A. Flach, Raúl Santos-Rodríguez
Reconciling Training and Evaluation Objectives in Location Agnostic Surrogate Explainers. CIKM (2023)
Katarzyna Stawarz, Dmitri S. Katz, Amid Ayobi, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making. Int. J. Hum. Comput. Stud. 173 (2023)
Tashi Namgyal, Peter A. Flach, Raúl Santos-Rodríguez
MIDI-Draw: Sketching to Control Melody Generation. CoRR (2023)
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. 112 (9) (2023)
Yu Chen, Peter A. Flach
Self-Enhancer: A Self-supervised Framework for Low-Supervision, Drifted Data with Significant Missing Values. ICANN (4) (2022)
Peter A. Flach
Empirical Evaluation of Predictive Models: A keynote at ECIR 2022. SIGIR Forum 56 (1) (2022)
Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
The Weak Supervision Landscape. PerCom Workshops (2022)
Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
The Weak Supervision Landscape. CoRR (2022)
Peter A. Flach, Kacper Sokol
Simply Logical - Intelligent Reasoning by Example (Fully Interactive Online Edition). CoRR (2022)
Taku Yamagata, Raúl Santos-Rodríguez, Robert J. Piechocki, Peter A. Flach
Understanding Reinforcement Learning Based Localisation as a Probabilistic Inference Algorithm. ICANN (2) (2022)
Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency. Softw. Impacts 14 (2022)
Torty Sivill, Peter A. Flach
LIMESegment: Meaningful, Realistic Time Series Explanations. AISTATS (2022)
Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. CoRR (2022)
Reem Alotaibi, Peter A. Flach
Multi-label thresholding for cost-sensitive classification. Neurocomputing 436 (2021)
Yu Chen, Song Liu, Tom Diethe, Peter A. Flach
Continual Density Ratio Estimation in an Online Setting. CoRR (2021)
Kacper Sokol, Peter A. Flach
You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source. CoRR (2021)
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
Classifier Calibration: How to assess and improve predicted class probabilities: a survey. CoRR (2021)
Hao Song, Peter A. Flach
Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing. Int. J. Interact. Multim. Artif. Intell. 6 (5) (2021)
Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning. IUI Workshops (2021)
Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies. Proc. ACM Hum. Comput. Interact. 5 (CSCW2) (2021)
Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach
Human Activity Recognition Based on Dynamic Active Learning. IEEE J. Biomed. Health Informatics 25 (4) (2021)
Kacper Sokol, Peter A. Flach
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence. CoRR (2021)
Fernando Martínez-Plumed, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana, Peter A. Flach
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories. IEEE Trans. Knowl. Data Eng. 33 (8) (2021)
Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control. CoRR (2020)
Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodríguez, Tijl De Bie, Peter A. Flach
FACE: Feasible and Actionable Counterfactual Explanations. AIES (2020)
Haixia Bi, Raúl Santos-Rodríguez, Peter A. Flach
Polsar Image Classification via Robust Low-Rank Feature Extraction and Markov Random Field. IGARSS (2020)
Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
Model-Based Reinforcement Learning for Type 1 Diabetes Blood Glucose Control. AAI4H@ECAI (2020)
Kacper Sokol, Peter A. Flach
Towards Faithful and Meaningful Interpretable Representations. CoRR (2020)
Yu Chen, Tom Diethe, Peter A. Flach
Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning. CoRR (2020)
Kacper Sokol, Peter A. Flach
One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency. CoRR (2020)
Michael Holmes, Miquel Perelló-Nieto, Hao Song, Emma Tonkin, Sabrina Grant, Peter A. Flach
Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery. J. Heal. Informatics Res. 4 (3) (2020)
Kacper Sokol, Peter A. Flach
LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees. CoRR (2020)
Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. J. Open Source Softw. 5 (49) (2020)
Kacper Sokol, Peter A. Flach
One Explanation Does Not Fit All. Künstliche Intell. 34 (2) (2020)
Peter A. Flach
Reflections on reciprocity in research. Mach. Learn. 109 (7) (2020)
Marvin Meeng, Harm de Vries, Peter A. Flach, Siegfried Nijssen, Arno J. Knobbe
Uni- and multivariate probability density models for numeric subgroup discovery. Intell. Data Anal. 24 (6) (2020)
Kacper Sokol, Peter A. Flach
Explainability fact sheets: a framework for systematic assessment of explainable approaches. FAT* (2020)
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
Distribution Calibration for Regression. CoRR (2019)
Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach
bLIMEy: Surrogate Prediction Explanations Beyond LIME. CoRR (2019)
Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodriguez, Tijl De Bie, Peter A. Flach
FACE: Feasible and Actionable Counterfactual Explanations. CoRR (2019)
Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach
$β^3$-IRT: A New Item Response Model and its Applications. AISTATS (2019)
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. CoRR (2019)
Cèsar Ferri, José Hernández-Orallo, Peter A. Flach
Setting decision thresholds when operating conditions are uncertain. Data Min. Knowl. Discov. 33 (4) (2019)
Niall Twomey, Haoyan Chen, Tom Diethe, Peter A. Flach
An application of hierarchical Gaussian processes to the detection of anomalies in star light curves. Neurocomputing 342 (2019)
Kacper Sokol, Peter A. Flach
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches. CoRR (2019)
Peter A. Flach
Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward. AAAI (2019)
Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach
HyperStream: a Workflow Engine for Streaming Data. CoRR (2019)
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. NeurIPS (2019)
Kacper Sokol, Peter A. Flach
Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals. AAAI (2019)
Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency. CoRR (2019)
Tom Wilcox, Nanlin Jin, Peter A. Flach, Joshua Thumim
A Big Data platform for smart meter data analytics. Comput. Ind. 105 (2019)
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
Distribution calibration for regression. ICML (2019)
Kacper Sokol, Peter A. Flach
Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety. SafeAI@AAAI (2019)
Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach
-IRT: A New Item Response Model and its Applications. CoRR (2019)
Mike Holmes, Hao Song, Emma Tonkin, Miquel Perelló-Nieto, Sabrina Grant, Peter A. Flach
Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild. KHD@IJCAI (2018)
Kacper Sokol, Peter A. Flach
Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant. IJCAI (2018)
Haoyan Chen, Tom Diethe, Niall Twomey, Peter A. Flach
Anomaly detection in star light curves using hierarchical Gaussian processes. ESANN (2018)
Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. KDD (2018)
Fernando Martínez-Plumed, Bao Sheng Loe, Peter A. Flach, Seán Ó hÉigeartaigh, Karina Vold, José Hernández-Orallo
The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI. IJCAI (2018)
Peter A. Flach, Myra Spiliopoulou, Serge Allegrezza, Matthias Böhmer, Burkhard Hess, Berthold Lausen
Introduction to the special issue on Data Science in Europe. Int. J. Data Sci. Anal. 6 (3) (2018)
Kacper Sokol, Peter A. Flach
Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements. IJCAI (2018)
Niall Twomey, Tom Diethe, Xenofon Fafoutis, Atis Elsts, Ryan McConville, Peter A. Flach, Ian Craddock
A Comprehensive Study of Activity Recognition Using Accelerometers. Informatics 5 (2) (2018)
Hao Song, Meelis Kull, Peter A. Flach
Non-Parametric Calibration of Probabilistic Regression. CoRR (2018)
Przemyslaw Woznowski, Emma Tonkin, Peter A. Flach
Activities of Daily Living Ontology for Ubiquitous Systems: Development and Evaluation. Sensors 18 (7) (2018)
Simon Price, Peter A. Flach
Computational support for academic peer review: a perspective from artificial intelligence. Commun. ACM 60 (3) (2017)
Fernando Martínez-Plumed, Lidia Contreras Ochando, César Ferri, Peter A. Flach, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana
CASP-DM: Context Aware Standard Process for Data Mining. CoRR (2017)
Niall Twomey, Tom Diethe, Ian Craddock, Peter A. Flach
Unsupervised learning of sensor topologies for improving activity recognition in smart environments. Neurocomputing 234 (2017)
Tom Diethe, Niall Twomey, Meelis Kull, Peter A. Flach, Ian Craddock
Probabilistic Sensor Fusion for Ambient Assisted Living. CoRR (2017)
Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach
Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. AISTATS (2017)
Kacper Sokol, Peter A. Flach
The Role of Textualisation and Argumentation in Understanding the Machine Learning Process. IJCAI (2017)
Yu Chen, Tom Diethe, Peter A. Flach
ADL™: A Topic Model for Discovery of Activities of Daily Living in a Smart Home. IJCAI (2016)
José Hernández-Orallo, Adolfo Martínez Usó, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach, Chowdhury Farhan Ahmed, Nicolas Lachiche
Reframing in context: A systematic approach for model reuse in machine learning. AI Commun. 29 (5) (2016)
Niall Twomey, Tom Diethe, Meelis Kull, Hao Song, Massimo Camplani, Sion L. Hannuna, Xenofon Fafoutis, Ni Zhu, Pete Woznowski, Peter A. Flach, Ian Craddock
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. CoRR (2016)
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
Declaratively Capturing Local Label Correlations with Multi-Label Trees. ECAI (2016)
Hao Song, Meelis Kull, Peter A. Flach, Georgios Kalogridis
Subgroup Discovery with Proper Scoring Rules. ECML/PKDD (2) (2016)
Tom Diethe, Niall Twomey, Peter A. Flach
BDL.NET: Bayesian dictionary learning in Infer.NET. MLSP (2016)
Niall Twomey, Tom Diethe, Peter A. Flach
On the need for structure modelling in sequence prediction. Mach. Learn. 104 (2-3) (2016)
Tom Diethe, Niall Twomey, Peter A. Flach
Active transfer learning for activity recognition. ESANN (2016)
Reem Al-Otaibi, Nanlin Jin, Tom Wilcox, Peter A. Flach
Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data. IEEE Trans. Ind. Informatics 12 (2) (2016)
Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. KDD (2016)
Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown
Cost-sensitive boosting algorithms: Do we really need them? Mach. Learn. 104 (2-3) (2016)
Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach
Background Check: A General Technique to Build More Reliable and Versatile Classifiers. ICDM (2016)
Kacper Sokol, Peter A. Flach
Activity Recognition in Multiple Contexts for Smart-House Data. ILP (Short Papers) (2016)
Ni Zhu, Tom Diethe, Massimo Camplani, Lili Tao, Alison Burrows, Niall Twomey, Dritan Kaleshi, Majid Mirmehdi, Peter A. Flach, Ian Craddock
Bridging e-Health and the Internet of Things: The SPHERE Project. IEEE Intell. Syst. 30 (4) (2015)
Reem Al-Otaibi, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach
Versatile Decision Trees for Learning Over Multiple Contexts. ECML/PKDD (1) (2015)
Peter A. Flach, Meelis Kull
Precision-Recall-Gain Curves: PR Analysis Done Right. NIPS (2015)
Chowdhury Farhan Ahmed, Md. Samiullah, Nicolas Lachiche, Meelis Kull, Peter A. Flach
Reframing in Frequent Pattern Mining. ICTAI (2015)
Meelis Kull, Peter A. Flach
Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration. ECML/PKDD (1) (2015)
Megha Agarwal, Peter A. Flach
Activity recognition using conditional random field. iWOAR (2015)
Yu Chen, Peter A. Flach
SVR-based Modelling for the MoReBikeS Challenge: Analysis, Visualisation and Prediction. DC@PKDD/ECML (2015)
Hao Song, Peter A. Flach
Model Reuse with Subgroup Discovery. DC@PKDD/ECML (2015)
Tom Diethe, Niall Twomey, Peter A. Flach
Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics. ECML/PKDD (2) (2015)
Cèsar Ferri Ramirez, Peter A. Flach, Nicolas Lachiche
Report of the First International Workshop on Learning over Multiple Contexts (LMCE 2014). SIGKDD Explor. 17 (1) (2015)
Meelis Kull, Peter A. Flach
Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy. ECML/PKDD (2) (2014)
Nanlin Jin, Peter A. Flach, Tom Wilcox, Royston Sellman, Joshua Thumim, Arno J. Knobbe
Subgroup Discovery in Smart Electricity Meter Data. IEEE Trans. Ind. Informatics 10 (2) (2014)
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion. ICMLA (2014)

Peter A. Flach.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Peter A. Flach